Created by: qingqing01

The image processing is a key step for CNN. It's slower when reading image list directly by PyDataProvider. And this leads to a lower speedup on Multi-GPUs, especially on 8 GPUs or 16 GPUs.

This PR has two features:

1. A C++ accelerated library that can be called by Python: OpenCV + Multi-threads
2. A Python module with python-multiprocessing and Python-OpenCV

One can select one of them to use.

The performance on 4 GPUs( K40 ) with input size 224 * 224 *3 is as follows. 实验条件：

• 4 Tesla K40m
• 总batch size: 192
• 下面时间为20个mini-Batch的时间

1. PIL直接读取图片list: 64.8s
2. Pickle对数据打Batch再读取：46.8s
3. 数据打Batch + Python多进程 + Python-OpenCV: 29.7s
4. 数据打Batch + C++多线程 + OpenCV: 26.7s

下一个PR增加使用文档。

#457 (closed)